Original article


Using the cytokinesis-block micronucleus cytome assay to evaluate chromosomal DNA damage in chronic renal patients undergoing bicarbonate haemodialysis

and haemodiafiltration

  1. Guido1, A. ZiZZA2, M.R. TuMolo2, G. STefAnelli3, M. d’AlbA4, A. idolo1, f. bAGoRdo1, f. SeRio1, T. GRASSi1,

    1. de donno1

1 laboratory of Hygiene, department of biological and environmental Sciences and Technologies, university of Salento, lecce, italy; 2 institute of Clinical Physiology, national Research Council, lecce, italy; 3 nephrology & dialysis Special unit, “i. Veris delli Ponti” Hospital, Scorrano, lecce local Health unit, italy; 4 dialysis Special unit, “f. Pispico” Hospital, Poggiardo, lecce local Health unit, italy


Keywords

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Chronic Renal Failure (CRF) • DNA damage • Micronucleus (MN)


Summary

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Introduction. Chronic Renal Failure (CRF) patients are consid- ered to show genomic instability and are associated with a high risk of both cardiovascular diseases and cancer. We explored DNA damage due to two dialysis treatments in 20 patients undergoing bicarbonate haemodialysis (BD), 20 undergoing haemodiafiltra- tion (HDF) and 40 healthy subjects.

Methods. The cytokinesis-block micronucleus (MN) assay was per- formed on peripheral blood lymphocytes to evaluate genetic damage. Results. A higher frequency of MN in the dialysis groups com-

pared with controls was found. The results do not show a rela- tionship between genetic instability and the type, frequency and duration of haemodialysis. The average BD and HDF treatment time was respectively 3.8 ± 6.3 and 3.7 ± 3.9 yrs. CAT and scin- tigraphy was independently correlated with high levels of MN. Conclusions. Overall, the frequency of MN in CRF patients undergoing dialysis therapy was observed to be higher. Further studies need to be performed on a larger number of patients and for a longer period.



Introduction


Chronic Renal Failure (CRF) is a progressive disease with loss of kidney function over time [1]. The early stages of CRF (stages 2 and 3) are characterized by a decrease in the glomerular filtration rate (the best pa- rameter for categorising kidney function) and are gen- erally asymptomatic. Advanced stages of the disease (4 and 5) are manifested by a severely decreased glomeru- lar filtration rate accompanied by clinical complications (hypertension, anaemia, bone disease), requiring renal replacement therapy when end-stage renal disease is reached [2].

CRF patients, regardless of whether they are receiving dialysis, present a high risk of cardiovascular patholo- gies and cancer (mainly cervical, bladder, thyroid, and renal cell carcinoma) [3-5], as well as elevated levels of genetic damage [6, 7]. This extensive damage may be related to impairment of DNA repair. DNA lesions may induce mutations in tumour-suppressors and oncogenes that may lead to malignancies if mutagenicity is not mit- igated by repair mechanisms [8].

Uraemia, microinflammation and oxidative stress [free radicals, reactive oxygen species (ROS), etc] are the main mechanisms underlying this phenomenon [6].


Indeed, evidence indicates that end-stage renal disease is associated with oxidative stress, as a result of both increased production of oxidants and weaker antioxidant defences [9-11].

This situation is aggravated by a series of events induced by dialysis treatment. Continuous contact of peripheral blood with dialysis membranes promotes the activa- tion of leukocytes that produce various inflammatory mediators (e.g. complement and platelet-activating fac- tor) [12].

Renal Replacement Therapies (RRT) involve peritoneal (or intracorporeal) dialysis, which is a blood-filtering method that uses the peritoneum, the serous membrane that lines the abdominal wall, to allow exchanges be- tween blood and dialysis fluid, and extracorporeal dialy- sis or haemodialysis, in which blood circulates outside the body, using an artificial membrane in an external fil- ter to remove waste products [13].

The types of dialysis treatment respond to different ther- apeutic needs, specifically the type and size of toxic mol- ecules to be removed. Diffusive and diffusive-convective techniques are both currently used [14]. The former in- clude Acetate and Bicarbonate Dialysis (BD), while the latter include Haemodiafiltration (HDF), an innovative diffusive-convective blood purification treatment devel-

oped from BD, consisting of a combination of Haemofil- tration (HF) and conventional Haemodialysis (HD) [15]. HDF combines the advantages of the diffusive method of removing low molecular weight solutes with those of convective treatment, which removes substances with medium/high molecular weight [16, 17].

Several studies have found high levels of genetic dam- age in patients with CRF suffering from uraemia and oxidative stress, detected by methods such as sister- chromatid exchange, the comet test and micronucleus assays [8, 18, 19]. Indeed, both CRF and the long-term HD therapy used to treat it can cause genomic dam- age, leading to single and double-strand breaks, alka- li-labile sites and formation of micronuclei (MN), in addition to reduction of DNA repair capacity [18, 20]. MN are DNA-containing particles that occur during mitosis and result from unrepaired DNA double-strand breaks, leading to chromatin fragments or whole chro- mosomes being distributed incorrectly. MN frequency is considered a good surrogate biomarker for detecting genetic damage and evaluating cancer risk [21, 22]. The MN assay is performed on human lymphocytes because they are excellent markers of exposure; they circulate for years or even decades through different organs and accumulate DNA damage during their lifespan [23-25]. The aim of the present study is to evaluate DNA dam- age in CRF patients undergoing BD and HDF dialysis techniques compared with a control group, by evaluating MN frequency in peripheral blood lymphocytes (PBL).


Methods


Subjects. The study was carried out on a total of 80 in- dividuals including 40 CRF patients (20 undergoing BD and 20 undergoing HDF) and 40 healthy controls.

Patients aged less than 18 years, pregnant, with ma- lignancies, with bacterial or viral infections, hepatic impairment, or undergoing treatment with anti-inflam- matory agents, cytostatics or immunosuppressive drugs were excluded. Healthy volunteers who did not meet the exclusion criteria served as control subjects.

All participants in the study were recruited at the “I. Veris Delli Ponti” hospital in Scorrano from May 2013 to December 2014 and completed a questionnaire re- questing general details and information on smoking habits, alcohol intake, occupational exposure and risk factors for cancer.

This study was approved by the local institutional Eth- ics Committee and informed consent was obtained from each patient enrolled.

Lymphocyte Culture and Cytokinesis-Block Micro- nucleus (CBMN) Cytome Assay. Blood samples were obtained for each subject by venipuncture using heparin- ized vacutainers and sent directly to the Laboratory of Hygiene of University of Salento.

300 μl of blood sample was added to 4.7 ml of Karyotyp- ing medium. At 44-h incubation, 100 μl of cytochalasin B was added to the culture to arrest cytokinesis.

After 28-h incubation, the cultures were harvested by cen-

trifugation at 2000 rpm for 4 min at 25°C and treated with a hypotonic solution (112 mg KCl/20 ml of deionized water) for 10 min. The supernatant was discarded after each cen- trifugation, leaving approximately 0.5 ml of suspension.

0.4 ml of acetic acid/methanol (5:3) solution was added to the culture 10 min later. The cells were centrifuged again and 5 ml of methanol was added. After a further centrifu- gation, the cell suspension was twice fixed in a methanol/ acetic acid solution (7:1) and then centrifuged again. The tubes were then placed in a freezer for two hours. The pel- let was resuspended and 3 drops were placed on a clean slide kept at -20°C. The slides were stained with Giemsa solution. Afterwards, they were washed with distilled wa- ter and left to dry overnight.

For each sample, 1000 binucleated cells were scored un- der optical microscope for MN analysis, following the criteria for determining MN [26]. We evaluated MN fre- quency as the number of micronucleated cells per 1000 cells (‰). To avoid differences between observers, the same individual carried out the microscopic analyses.

The Nuclear Division Index (NDI), a cell proliferation index, was calculated by scoring mono-, bi-, tri- and tetranucleated cells in accordance with Eastmond and Tucker [27].

Statistical analysis. All analyses were performed using SPSS 18.0 (Chicago, USA). Continuous variables were expressed as mean ± standard deviation (SD), whereas categorical variables were expressed in absolute and per- centage values.

For continuous variables, differences between groups were compared by the Mann-Whitney test and 1-way Analysis of Variance (ANOVA), where applicable. Ho- mogeneity of variance was evaluated using the Levene test. ANOVA was performed with a Brown-Forsythe adjustment for heteroscedasticity, and with a post-hoc Tukey test or Dunnett’s T3 procedure for multiple com- parisons of unequal variances in order to determine which groups differ from the others.

Pearson’s chi-square and the likelihood ratio chi-square were used for proportions.

Univariate and multivariate logistic regression analyses were performed to examine predictors of abnormal MN frequency. Variables that proved to be associated with higher MN frequency (p < 0.25) in univariate analyses were inserted in a multivariate logistic regression model in order to investigate independent predictors of high frequency. Stepwise regression analysis was performed in order to select the variables adopted in the multivari- ate model. For all analyses, a p-value of < 0.05 was con- sidered to be statistically significant.


Results


The demographic characteristics and risk factors of CRF patients and healthy controls are shown in Table I. The average age of the control group was lower (53.2 ± 10.2) than that of patients treated by BD (57.0 ± 12.0) and HDF (59.8 ± 10.1), although the differences were not statistically significant. The differences between patients

Tab. I. Characteristics of patients with bicarbonate hemodialysis (group 1), hemodiafiltration (group 2), and control group.


Group 1

(n = 20)

Group 2

(n = 20)

p-value

Control Group (n = 40)

p-value

Age (± Sd)

57.0 ± 12.0

59.8 ± 10.1

0.685*

53.2 ± 10.2

0.075**

gender, male, n (%)

12 (60.0)

13 (65.0)

0.774^

27 (64.7)

0.623^^

risk factors

diagnostic test

radiography, n (%)

18 (90.0)

16 (80.0)

0.661^

38 (95.0)

0.074

CAT, n (%)

12 (60.0)

11 (55.0)

0.927^

7 (17.5)

0.749^^

Scintigraphy, n (%)

17 (85.0)

13 (65.0)

0.273^

1 (2.9)

0.000^^

Angiography, n (%)

4 (20.0)

5 (25.0)

0.519^

0 (-)

0.001^^

mammography, n (%)

8 (40.0)

6 (30,0)

0.921^

3 (8.8)

0.006^^

radiotherapy, n (%)

0 (-)

0 (-)

-

0 (-)

-

mrI, n (%)

0 (-)

1 (5,0)

1.000^

8 (20.0)

0.235^^

echography, n (%)

20 (100)

20 (100)

1.000^

18 (45.0)

1.000^^

Smoke, n (%)

13 (65.0)

6 (30,0)

0.057^

14 (35.0)

0.025^^

years of smoking (± Sd)

17.9 ± 7.2

15.5 ± 6.3

0.848*

16.3 ± 10.7

0.829**

Alcohol (all), n (%)

Wine

15 (78.9)

15 (78.9)

0.715^

12 (30.0)

0.000^^

Beer

16 (84.2)

14 (73.7)

0.715^

12 (30.0)

0.000^^

Spirits

6 (31.6)

2 (10.5)

0.236^

7 (17.5)

0.262^^

diabetes, n (%)

3 (15.0)

6 (30.0)

0.449^

0 (-)

0.000^^

hypertension, n (%)

15 (75.0)

17 (85.0)

0.693^

5 (12.5)

0.000^^

Intercontinental travel, n (%)

1 (5.0)

1 (6,70)

0.468^

2 (5.0)

1.000^^

mobile phone repeaters, n (%)

0 (-)

0 (-)

-

6 (15.0)

0.012^^

residential area

Town centre, n (%)

13 (65.0)

13 (65.0)

0.497^

16 (41.2)

0.001^^

Suburban, n (%)

3 (15.0)

1 (5.0)

20 (50.0)

rural area, n (%)

4 (20.0)

6 (30.0)

4 (8.8)

plan home

ground floor, n (%)

14 (70.0)

16 (80.0)

0.344^

18 (44.1)

0.016^^

First floor, n (%)

2 (10.0)

3 (15.0)

17 (42.5)

Second floor n (%)

4 (20.0)

1 (5.0)

5 (11.8)

education level

primary school, n (%)

9 (45.0)

6 (30.0)

0.290^

1 (2.5)

0.000^^

Secondary school, n (%)

8 (4.0)

16 (30.0)

14 (35.0)

high school diploma, n (%)

2 (10.0)

6 (30.0)

15 (37.5)

degree, n (%)

1 (5.0)

2 (10.0)

10 (25.0)

professional exposure

Ionizing radiation, n (%)

0 (-)

0 (-)

-

0 (-)

-

pesticides, n (%)

0 (-)

0 (-)

-

0 (-)

-

Chemicals, n (%)

0 (-)

0 (-)

-

6 (11.8)

0.012^^

heavy metals, n (%)

0 (-)

0 (-)

-

0 (-)

-

Anesthetic gases, n (%)

7 (35.0)

7 (35.0)

0.740^

1 (2.9)

0.056^^

Surgery, n (%)

7 (35.0)

8 (40.0)

1.000^

13 (32.5)

0.849^^

Kidney transplant, n (%)

4 (20.0)

1 (5.0)

0.442^

0 (-)

-

Time hemodialysis

≤ 5 years, n (%)

16 (80.0)

16 (80.0)

0,675^

0 (-)

-

> 5 years, n (%)

4 (20.0)

4 (20.0)

0 (-)

Frequency hemodialysis

3 time a week

1 (5.0)

7 (35.0)

0.048^

0 (-)

-

> 3 time a week

19 (95.0)

13 (65.0)

0 (-)

Kidney failure

glomerulonephritis, n (%)

8 (40.0)

5 (25.0)

0.399^

0 (-)

-

Nephroangiosclerosis, n (%)

5 (25.0)

5 (25.0)

0 (-)

diabetic nephropathy, n (%)

3 (15.0)

7 (35.0)

0 (-)

Urethral reflux, n (%)

0 (-)

2 (10.0)

0 (-)

polycystic kidney, n (%)

1 (5.0)

1 (5.0)

0 (-)


Group 1

(n = 20)

Group 2

(n = 20)

p-value

Control Group (n = 40)

p-value

ANCA vasculitis, n (%)

1 (5.0)

0 (-)

0 (-)

malformation uropathy, n (%)

1 (5.0)

0 (-)

0 (-)

Chronic rejection, n (%)

1 (5.0)

0 (-)

0 (-)

Legend: Sd, Standard deviation; CAT, Computed Axial Tomography, mrI, magnetic resonance Imaging.

* hSd di Tukey

** ANOvA

^ pearson’s χ2 test

^^ Likelihood ratio chi-square


Tab. II. Cytogenetic parameters in the studied populations.


Group 1

Group 2

Control Group

N

Mean ± SD

(median)

N

Mean ± SD

(median)

N

Mean ± SD

(median)

p-value

mN/1,000

men

12

14.25 ± 9.77

(13.50)

13

13.77 ± 6.76

(14.00)

28

5.88 ± 2.86

(5.00)

0.002*

Women

8

13.63 ± 5.15

(15.50)

7

23.86 ± 9.25

(23.00)

12

7.67 ± 1.97

(8.00)

0.009*

Total

20

14.0 ± 8.07

(14.50)

20

17.30 ± 8.96

(15.50)

40

5.88 ± 2.86

(6.00)

0.001*

Time of hemodialysis

5 years

16

14.2 ± 8.83

(14.50)

16

18.2 ± 9.52

(18.00)

-

-

-

0.775^

> 5 years

4

13.2 ± 4.65

(14.00)

4

13.7 ± 5.80

(14.50)

-

-

-

0.725^

p = 0.841^

p = 0.390^

Frequency of hemodialysis

3 time a week

19

13.8 ± 8.24

(14.00)

13

18.4 ± 6.33

(20.00)

-

-

-

0.355

> 3 time a week

1

18.0

(-)

7

15.3 ± 12.91

(9.00)

-

-

-

-

p = -

p = 0.567^

NdI

men

12

5.69 ± 4.71

(5.61)

13

4.25 ± 2.98

(4.01)

28

1.14 ± 1.18

(0.58)

0.003*

Women

8

2.65 ± 2.82

(2.10)

7

4.71 ± 4.48

(3.14)

12

1.39 ± 1.92

(0.57)

0.258*

Total

20

4.47 ± 4.26

(3.08)

20

4.41 ± 3.47

(3.58)

40

0.94 ± 1.31

(0.58)

0.001*

Legend: Sd, Standard deviation; mN, micronucleus; NdI, Nuclear division Index.

*ANOvA was performed with a Brown-Forsythe adjustment for heteroscedasticity and with dunnett’s T3 procedure for multiple comparisons of unequal variances.

^ Test U di mann-Whitney.


Tab. III. Univariate and multivariate logistic regression analysis demonstrating the relationship of micronucleus (mN) frequency with most im- portant experimental variables in dialysis patients.


Univariate

Multivariate

OR (95% CI)

p

OR (95% CI)

p

Age (± Sd)

1.14 (0.51-2.58)

0.742

-

gender, male, n (%)

2.43 (0.65-9.07)

0.183

2.19 (0.14-34.90)

0.577

risk factors

diagnostic test

- radiography, n (%)

1.40 (0.22-8.72)

0.715

-

- CAT, n (%)

2.20 (0.58-8.28)

0.236

7.31 (0.90-59.30)

0.062

- Scintigraphy, n (%)

0.33 (0.08-1.46)

0.139

0.09 (0.01-1.01)

0.051

- Angiography, n (%)

1.27 (0.28-5.68)

0.758

-

- mammography, n (%)

1.89 (0.50-7.09)

0.345

-

Smoke, n (%)

0.51 (0.14-1.85)

0.299

-

Alcohol

- Wine

0.33 (0.08-1.46)

0.139

12.10 (0.00-0.00)

0.997

- Beer, n (%)

0.18 (0.04-0.88)

0.026

0.00 (0.00-0.00)

0.996

- Spirits, n (%)

0.43 (0.07-2.46)

0.321

-

diabetes, n (%)

3.00 (0.69-13.12)

0.139

4.10 (0.38-44.79)

0.247

hypertension, n (%)

1.84 (0.31-10.92)

0.489

-


Univariate

Multivariate

Intercontinental travel, n (%)

1.53 (0.09-26.43)

0.769

-

Residential area

- Town centre, n (%)

0.83 (0.22-3.12)

0.787

-

- Suburban, n (%)

5.31 (0.50-56.39)

0.134

10.06 (0.27-377.53)

0.212

- Rural area, n (%)

0.56 (0.12-2.60)

0.450

-

Plan home

- Ground floor, n (%)

9.00 (1.01-80.13)

0.016

4.63 (0.14-155.21)

0.392

- First floor, n (%)

0.00 (0.00-0.00)

0.018

0.00 (0.00-0.00)

0.995

- Second floor n (%)

0.33 (0.03-3.30)

0.309

-

Education level

- Primary school, n (%)

1.56 (0.42-5.72)

0.506

-

- Secondary school, n (%)

0.47 (0.12-1.88)

0.273

-

- High school diploma, n (%)

0.88 (0.18-4.32)

0.871

-

- Degree, n (%)

3.29 (0.27-39.66)

0.332

-

Professional exposure

- Anesthetic gases, n (%)

0.76 (0.20-2.90)

0.684

-

- Surgery, n (%)

0.64 (0.17-2.41)

0.502

-

Kidney transplant, n (%)

0.33 (0.03-3.30)

0.309

-

Type of hemodialysis, n (%)

1.52 (0.42-5.43)

0.518

Time hemodialysis

0.43 (0.07-2.46)

0.321

-

Frequency hemodialysis

0.88 (0.18-4.32)

0.871

-

Kidney failure

- Glomerulonephritis, n (%)

0.56 (0.14-2.26)

0.404

-

- Nephroangiosclerosis, n (%)

1.73 (0.41-7.33)

0.459

-

- Diabetic nephropathy, n (%)

3.00 (0.69-13.12)

0.139

4.10 (0.37-44.79)

0.247

- Urethral reflux, n (%)

1.53 (0.09-26.43)

0.769

-


Legend: OR, Odds Ratio; SD, Standard Deviation; CAT, Computed Axial Tomography, MRI, Magnetic Resonance Imaging.

Variables showing a tendency of association with abnormal MN frequency (p < 0.25) in the univariate analysis were included in the multivariate model.


on dialysis and controls are linked to the difficulty of re- cruiting healthy individuals of the same age as patients. The risk factor analysis showed no significant difference between the two groups of patients undergoing dialysis, while highly significant differences emerged among the three groups in terms of their exposure to scintigraphy (p < 0.000), angiography (p < 0.001), mammography (p < 0.006), mobile phone repeaters (p < 0.012) and chemicals (p < 0.012), as well as cigarette smoking (p

< 0.025), wine and beer consumption (both p < 0.000), diabetes (p < 0.000), hypertension (p < 0.000), residen- tial area (p < 0.001), storey of residence (i.e. ground floor, first floor, etc.) (p < 0.016) and level of education (p < 0.000).

The results of the MN assays on PBL show significantly higher frequency in the groups on dialysis than controls (p < 0.001), in both males (p < 0.002) and females (p

< 0.009) (Tab. II). No difference was observed between BD and HDF patients and no correlation was observed between the number of MN and the duration or weekly frequency of treatment.

In addition, as a measure of cytotoxicity, NDI was found to be significantly lower in the control group (p < 0.001) than BD and HDF-treated patients. The frequency of MN was significantly higher in men (p < 0.003) than women (p < 0.258) (Tab. II).

Table III shows the results of the univariate and multi- variate logistic regression analyses, demonstrating rela-

tionships between MN and other variables. Univariate analysis revealed that CAT, scintigraphy, wine and beer consumption, diabetes, residence in the suburbs, storey of residence, and diabetic nephropathy are significantly associated with high MN frequency. However, only CAT and scintigraphy independently correlated with high MN frequency in a multivariate logistic regression model where the variables with p < 0.25 in the univariate anal- ysis were included as independent variables (Tab. III).


Discussion


Patients with Chronic Kidney Disease (CKD) have a higher risk of developing chronic degenerative diseases, such as coronary disease, strokes or transient ischemic attacks, heart failure, peripheral arterial disease, diabetes mellitus, hypertension, dyslipidemia, lung or liver dis- ease, cancer and dementia [28]. These adverse events are associated with severe cytogenetic damage [17].

In this study, damage was assessed by CBMN assay, in patients receiving two different dialysis treatments com- pared with a control group of healthy subjects. CBMN is the most frequently used chromosomal biomarker for evaluating MN frequency in PBL, which is a good sur- rogate marker of cancer risk [26].

It is assumed that CRF patients present high levels of genetic damage, but very little is known about the ori-

gins of this damage. Patients at all stages of CRF have greater oxidative stress than healthy people but it is even more severe in patients undergoing haemodialysis [29]. The problem of oxidative stress in patients on dialysis is mainly related to the accumulation of uraemic tox- ins and other endogenous substances with genotoxic properties [30]. The impairment of DNA damage re- pair is essentially caused by increased production of ROS [31-33]. CKD (which leads to the accumulation of metabolites) and haemodialysis (which removes me- tabolites) are among the factors associated with DNA damage [34].

Several studies, using a variety of techniques for the de- tection of chromosomal damage, have shown higher lev- els of genetic damage in CFR patients than controls [7, 8]. This was confirmed in the current study, in which a statistical difference in MN frequency between CFR patients and healthy volunteers was observed.

The degree of chromosome damage seems to be influ- enced by both the stage of CKD and the dialysis tech- nique used [19, 22], although studies show some disa- greement regarding the latter. Indeed some studies show a smaller degree of DNA damage in HD than BD, while others evince the opposite [35, 36]. Our study found no significant difference in oxidative damage between pa- tients receiving HD and BD.

Factors such as age, gender, tobacco and alcohol intake, diabetes, hypertension and level of education were not found to influence the genotoxic effect of haemodialysis treatment.

The univariate and multivariate logistic regression anal- yses showed that the risk factors associated with higher DNA damage are diagnostic procedures involving expo- sure to ionizing radiation (CAT and scintigraphy). Lit- erature data suggest that exposure to ionizing radiation induces the formation of MN and increases the risk of cancer and cardiovascular diseases [37, 38].

Some authors have shown that DNA damage correlates with the duration of dialysis treatment after more than 7 years [18, 22].

The results of this study show no relationship between genetic instability and the type and frequency of haemo- dialysis. In terms of the duration of treatment, the aver- age for the BD and HDF patients was respectively 3.8 ±

    1. and 3.7 ± 3.9 yrs, not sufficient to assess its relation- ship with genetic instability.

      Our results are consistent with the findings of Kan E et al., in which the average duration of dialysis treatment was approximately 3.5 years [39]. Another limitation of our study is the small sample size, which is not sufficient to distinguish between the DNA damage induced by the different treatments. Therefore, in order to expand this study, a larger number of patients, in treatment for more than 10 years, is required.

      In conclusion, the results of the research provide evi- dence that patients undergoing dialysis show a higher frequency of nuclear anomalies, resulting in alterations of genetic material as well as failures in repair mecha- nisms. Both CRF and the dialysis used to treat it can con- tribute to chromosomal and/or genomic damage, bearing

      in mind that the formation of MN mainly originates from acentric chromosome fragments or whole chromosomes secluded from daughter nuclei during mitosis.

      The severe DNA damage in CRF patients, exacerbated by the dialysis used to treat the condition, is relevant to the debate about possible intervention strategies to re- duce the risk of cancer and cardiovascular disease. The use of highly biocompatible membranes, ultrapure di- alysates and extracorporeal removal of ROS, as well as the many dietary antioxidants and pharmacological agents now being used to modulate the levels of genetic damage, need to be further investigated.


      Acknowledgments


      The authors are grateful to all subjects and patients for their participation in this study. All the authors declare no conflicts of interest.


      Authors’ Contributions


      MG, AZ, GS and ADD conceived, designed and coordi- nated the research. MD’A, AI, FS and TG collected data and samples. MG, AZ, MRT and MD’A performed the data quality control. MG and FB optimized the infor- matics database. MG performed the statistical analyses. MG, AZ, MRT, GS, MD’A and DDA evaluated the re- sults. MG, AZ and MRT wrote the manuscript. All Au- thors revised the manuscript and gave their contribution to improve the paper. All authors read and approved the final manuscript.


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n Received on December 8, 2015. Accepted on June 14, 2016.


n Correspondence: Antonella De Donno, Laboratory of Hygiene, Department of Biological and Environmental Sciences and Tech- nologies, University of Salento, via Prov. Lecce-Monteroni, 73100 Lecce, Italy - Tel. +39 0832 298687 - Fax +39 0832 298626 - E-

mail: antonella.dedonno@unisalento.it